Severe and multiple hypoglycemic episodes are associated with increased risk of death in ICU patients
Bibliographic record
Abstract
INTRODUCTION: In a randomized controlled trial comparing tight glucose control with a computerized decision support system and conventional protocols (post hoc analysis), we tested the hypothesis that hypoglycemia is associated with a poor outcome, even when controlling for initial severity. METHODS: We looked for moderate (2.2 to 3.3 mmol/L) and severe (<2.2 mmol/L) hypoglycemia, multiple hypoglycemic events (n ≥3) and the other main components of glycemic control (mean blood glucose level and blood glucose coefficient of variation (CV)). The primary endpoint was 90-day mortality. We used both a multivariable analysis taking into account only variables observed at admission and a multivariable matching process (greedy matching algorithm; caliper width of 10(-5) digit with no replacement). RESULTS: A total of 2,601 patients were analyzed and divided into three groups: no hypoglycemia (n =1,474), moderate hypoglycemia (n =874, 34%) and severe hypoglycemia (n =253, 10%). Patients with moderate or severe hypoglycemia had a poorer prognosis, as shown by a higher mortality rate (36% and 54%, respectively, vs. 28%) and decreased number of treatment-free days. In the multivariable analysis, severe (odds ratio (OR), 1.50; 95% CI, 1.36 to 1.56; P =0.043) and multiple hypoglycemic events (OR, 1.76, 95% CI, 1.31 to 3.37; P <0.001) were significantly associated with mortality, whereas blood glucose CV was not. Using multivariable matching, patients with severe (53% vs. 35%; P <0.001), moderate (33% vs. 27%; P =0.029) and multiple hypoglycemic events (46% vs. 32%, P <0.001) had a higher 90-day mortality. CONCLUSION: In a large cohort of ICU patients, severe hypoglycemia and multiple hypoglycemic events were associated with increased 90-day mortality. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT01002482 . Registered 26 October 2009.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".